Inverse radar sensor model and evidential grid mapping processors

Abstract

An example device includes motion sensing and processing circuitry to generate compensated motion data for a first time based on raw motion data and a set of motion indicators including a velocity indicator for the device calculated based on the raw motion data; a radar sensor to receive reflections indicating detections and generate data points for the first time representing the detections, in which each data point includes position and velocity information of a corresponding detection relative to the radar sensor; a first circuit to generate object data for the first time based on the set of the data points and the compensated motion data for the first time; and a second circuit to calculate, based on the object data for the first time and a characteristic of the radar sensor, for each cell in a grid representing an FOV of the radar sensor at the first time, probabilities of the cell being in a free state, a stationary state, and a dynamic state.

What is claimed is: 
     
         1 . A device comprising:
 a radar sensor configured to receive reflections indicating detections and generate data points representing the detections, in which each data point includes position and velocity information of a corresponding detection relative to the radar sensor; and   a processor coupled to the radar sensor configured to:
 receive, from the radar sensor, a set of the data points for time k; 
 receive motion data for time k indicative of motion of the device at time k; 
 generate object data for time k based on the set of the data points for time k and the motion data for time k, the object data representative of locations of the detections in a space, a radial velocity at each of the locations, and a signal-to-noise ratio (SNR) at each of the locations; and 
 calculate, based on the object data for time k and a characteristic of the radar sensor, for each cell in a grid representing a field of view (FOV) of the radar sensor at time k, probabilities of the cell being in a free state indicating no detected object in the cell, a stationary state indicating a stationary detected object in the cell, and a dynamic state indicating that a dynamic object is detected in the cell. 
   
     
     
         2 . The device of  claim 1 , further comprising:
 a motion sensor configured to output raw motion data for time k;   a motion calculator configured to:
 calculate a set of motion indicators including a velocity indicator for the device for time k based on the raw motion data for time k; and 
   a motion compensator configured to:
 determine a compensation for a radial velocity of the velocity indicator of the set of motion indicators for time k to generate a compensated set of motion indicators that represents the motion data for time k received by the processor. 
   
     
     
         3 . The device of  claim 2 , wherein the processor includes an inverse radar sensor model processor that includes:
 an object data calculator configured to generate the object data for time k; and   a state calculator configured to calculate the state probabilities at time k for each cell, and output the state probabilities calculated at time k of each cell.   
     
     
         4 . The device of  claim 3 , wherein the state calculator is configured to, for each cell in the grid, each cell being designated by (i,j):
 determine a probability of object occupancy of cell (i,j) at time k (Pocc(i,j;k)) based on a range of the cell (i,j) from the locations of the reflections;   determine a position of the cell (i,j) with respect to a position of the radar sensor;   update the Pocc(i,j;k) based on an ambiguity of the data points associated with the position of the cell (i,j); and   determine whether the Pocc(i,j;k) satisfies an occupancy criterion ∈occ.   
     
     
         5 . The device of  claim 4 , wherein:
 in response to the Pocc(i,j;k) not satisfying the ∈occ, perform a first set of operations; and   in response to the Pocc(i,j;k) satisfying the ∈occ, perform a second set of operations.   
     
     
         6 . The device of  claim 5 , wherein, to perform the first set of operations, the state calculator is configured to:
 determine whether the position of the cell (i,j) is between the position of the radar sensor and a position of a cell (a,b) with a corresponding Pocc(a,b;k) that satisfies the ∈occ;   in response to the position of the cell (i,j) not being between the radar sensor and the position of the cell (a,b) calculate, with low confidence, that the state of the cell (i,j) at time k is free; and   in response to the position of the cell (i,j) being between the radar sensor and the position of the cell (a,b) calculate, with high confidence, that the state of the cell (i,j) at time k is free.   
     
     
         7 . The device of  claim 5 , wherein, to perform the second set of operations, the state calculator is configured to:
 determine whether an adjusted radial velocity associated with the cell (i,j) satisfies a velocity criterion ∈v;   in response to the adjusted radial velocity not satisfying the ∈v, calculate a probability of cell (i,j) having the static state; and   in response to the radial velocity satisfying the ∈v, calculate a probability of cell (i,j) having the dynamic state.   
     
     
         8 . The device of  claim 1 , wherein the radar sensor characteristic includes at least one of:
 an antenna gain, and SNR of the radar sensor.   
     
     
         9 . The device of  claim 1 , further comprising:
 a grid mapping processor configured to:
 receive the calculated probabilities of each cell at the time k and state probabilities for each cell calculated during a time period 0:k−1 prior to time k; and 
 determine, for each cell, updated state probabilities for a time period 0:k based on the calculated probabilities of each cell at the time k and the state probabilities for each cell calculated during a time period 0:k−1 prior to time k. 
   
     
     
         10 . A system comprising:
 processing circuitry;   a non-transitory computer readable medium (CRM) storing executable code that, when executed by the processing circuitry, is configured to cause the system to:   receive reflections indicating detections and generate data points representing the detections, in which each data point includes position and velocity information of a corresponding detection relative to a radar sensor of the system;   receive, from the radar sensor, a set of the data points for time k;   receive motion data for time k indicative of motion of the radar sensor at time k;   generate object data for time k based on the set of the data points for time k and the motion data for time k, the object data representative of locations of the detections in a space, a radial velocity at each of the locations, and a signal-to-noise ratio (SNR) at each of the locations; and   calculate, based on the object data for time k and a characteristic of the radar sensor, for each cell in a grid representing a field of view (FOV) of the radar sensor at time k, probabilities of the cell being in a free state indicating no detected object in the cell, a stationary state indicating a stationary detected object in the cell, and a dynamic state indicating a dynamic object detected in the cell.   
     
     
         11 . The system of  claim 10 , wherein the executable code, when executed by the processing circuitry, is further configured to cause the system to:
 calculate a set of motion indicators including a velocity indicator for the system for time k based on a raw motion data for time k; and   determine a compensation for a component of the velocity indicator of the set of motion indicators for time k to generate a compensated set of motion indicators that represents the received motion data for time k.   
     
     
         12 . The system of  claim 10 , wherein each cell in the grid is designated by (i,j), and wherein the executable code, when executed by the processing circuitry, is further configured to cause the system to, for each cell in the grid:
 determine a probability of object occupancy of cell (i,j) at time k (Pocc(i,j;k)) based on a range of the cell (i,j) from the locations of the reflections;   determine a position of the cell (i,j) with respect to a position of the radar sensor;   update the Pocc(i,j;k) based on an ambiguity of the data points associated with the position of the cell (i,j); and   determine whether the Pocc(i,j;k) satisfies an occupancy criterion ∈occ.   
     
     
         13 . The system of  claim 12 , wherein the executable code, when executed by the processing circuitry, is further configured to cause the system to:
 in response to the Pocc(i,j;k) not satisfying the ∈occ, perform a first set of operations; and   in response to the Pocc(i,j;k) satisfying the ∈occ, perform a second set of operations.   
     
     
         14 . The system of  claim 13 , wherein the executable code, when executed by the processing circuitry, is further configured to cause the system to:
 determine whether the position of the cell (i,j) is between the position of the radar sensor and a position of a cell (a,b) with a corresponding Pocc(a,b;k) that satisfies the ∈occ;   in response to the position of the cell (i,j) not being between the radar sensor and the position of the cell (a,b) calculate, with low confidence, that the state of the cell (i,j) at time k is free; and   in response to the position of the cell (i,j) being between the radar sensor and the position of the cell (a,b) calculate, with high confidence, that the state of the cell (i,j) at time k is free.   
     
     
         15 . The system of  claim 13 , wherein the executable code, when executed by the processing circuitry, is further configured to cause the system to:
 determine whether an adjusted radial velocity associated with the cell (i,j) satisfies a velocity criterion ∈v;   in response to the adjusted radial velocity not satisfying the ∈v, calculate a probability of cell (i,j) having the static state; and   in response to the radial velocity satisfying the ∈v, calculate a probability of cell (i,j) having the dynamic state.   
     
     
         16 . A device comprising:
 motion sensing and processing circuitry configured to generate compensated motion data for a first time based on raw motion data and a set of motion indicators including a velocity indicator for the device calculated based on the raw motion data; and   a radar sensor configured to receive reflections indicating detections and generate data points for the first time representing the detections, in which each data point includes position and velocity information of a corresponding detection relative to the radar sensor;   a first circuit configured to generate object data for the first time based on the set of the data points for the first time and the compensated motion data for the first time; and   a second circuit configured to calculate, based on the object data for the first time and a characteristic of the radar sensor, for each cell in a grid representing a field of view (FOV) of the radar sensor at the first time, probabilities of the cell being in a free state indicating no detected object in the cell, a stationary state indicating a stationary detected object in the cell, and a dynamic state indicating that a dynamic object is detected in the cell.   
     
     
         17 . The device of  claim 16 , wherein the object data is representative of locations of the detections in a space, a radial velocity at each of the locations, and a signal-to-noise ratio (SNR) at each of the locations. 
     
     
         18 . The device of  claim 16 , wherein the first circuit includes:
 an object level data calculator configured to generate the object data for the first time; and   a state calculator configured to calculate the probabilities of the cell being in the free state, the stationary state, and the dynamic state.   
     
     
         19 . The device of  claim 16 , further comprising a third circuit configured to:
 receive the calculated probabilities and probabilities for each cell calculated during a time period prior to first time; and   determine, for each cell, updated state probabilities for a first time period including the first time based on the calculated probabilities of each cell at the first time and the state probabilities for each cell calculated during a second time period prior to the first time.   
     
     
         20 . The device of  claim 19 , wherein the third circuit includes a feedback loop.